Biomarkers in medicine最新文献

Aim: To investigate the dynamics of serum amyloid A (SAA) and procalcitonin (PCT) in sepsis-associated acute kidney injury (SAKI) and to evaluate their prognostic value for renal outcomes.

Methods: 159 Emergency Intensive Care Unit (EICU) patients with SAKI were enrolled. Serum SAA and PCT levels were measured on days 1, 3, 5, and 7 after enrollment. Patients were stratified by 28d renal recovery status. Associations with renal outcomes and predictive performance were examined using Pearson correlation, multivariable logistic regression and receiver operating characteristic (ROC) curve analysis.

Results: Non-recovery was associated with higher baseline levels of SAA, PCT, lactate, serum creatinine, and APACHE II scores (all p < 0.05). Both biomarkers declined progressively, reaching their lowest levels by day 7. Baseline SAA and PCT showed strong negative correlations with 28d eGFR (r = -0.414, -0.491; p < 0.05). Multivariable logistic regression identified APACHE II score (OR = 1.260), SAA (OR = 1.025), and PCT (OR = 1.275) as independent predictors of non-recovery. ROC curve analysis demonstrated good discriminative ability, with AUCs of 0.813 for SAA, 0.819 for PCT, and 0.827 for APACHE II (all p < 0.05).

Conclusion: SAA and PCT are robust short-term predictors of renal outcomes in sepsis-associated AKI. Their dynamic trajectories reflect disease severity and treatment response.

Aim: This study aimed to evaluate the impact of preprocedural neutrophil-to-albumin ratio (NAR) on survival among patients undergoing tunneled hemodialysis catheter (THC) placement.

Methods: We retrospectively reviewed 60 consecutive patients who underwent right-internal-jugular THC placement between July 2021 and October 2023. Demographics, laboratory variables and survival were collected. NAR and neutrophil-percentage-to-albumin ratio (NPAR) were calculated. Cox regression and Kaplan - Meier analyses explored associations with mortality; receiver-operating-characteristic (ROC) curves defined optimal cutoffs.

Results: Mean age was 70 ± 12 years; 24 patients (40%) died, yielding one-year survival of 62.5%. On multivariate Cox regression analysis, after adjustment for all covariates, higher NAR remained an independent predictor of mortality (p <0.001), together with older age and coronary artery disease. The ROC-derived NAR threshold of 175.4 produced an AUC of 0.813 (95% CI: 0.683-0.942). Patients with NAR >175.4 had markedly lower one-year survival than those below the threshold (30.2% vs 88.2%, p <0.001). Catheter patency at one year was 84.8%.

Conclusion: Among patients receiving a tunneled hemodialysis catheter, elevated preprocedural NAR levels were associated with increased mortality. NAR, which is an easily and routinely measurable parameter, may serve as a prognostic biomarker in this patient population.

Objectives: To investigate longitudinal changes in neuroimmune biomarkers during acute exacerbations of chronic obstructive pulmonary disease (AECOPD), their modulation by standard therapy, and prognostic implications for 90-day outcomes.

Materials and methods: In a prospective cohort, 266 hospitalized AECOPD patients were stratified into worsened (n = 53) and stable (n = 213) groups; 80 healthy individuals served as controls. Serum levels of BDNF, PD-1, MMP-9, and cytokines were assessed at admission (T1), pre-discharge (T2), and 90-day follow-up (T3). Mixed-effects models evaluated biomarker trajectories, while Cox regression examined correlations with clinical outcomes.

Results: Compared with controls, AECOPD patients exhibited higher IL-6, TNF-α, PD-1, and MMP-9, alongside reduced BDNF and IL-10. Stable patients demonstrated partial biomarker normalization, whereas worsened patients retained a pro-inflammatory profile. Corticosteroids and antibiotics attenuated cytokine elevations, and oxygen therapy facilitated BDNF recovery. Low BDNF and high MMP-9 predicted spirometric decline, while elevated PD-1 and MMP-9 were associated with increased 90-day readmission risk. A dual-axis model incorporating neurotrophic and immune exhaustion markers outperformed GOLD classification for risk prediction.

Conclusions: Neuroimmune biomarkers capture recovery heterogeneity in AECOPD. The proposed dual-axis model improves prognostic accuracy and may inform personalized management strategies.

Purpose: This meta-analysis aimed to evaluate the pan-cancer prognostic value of the neutrophil-to-lymphocyte ratio (NLR) for risk stratification in patients with cancer.

Methods: We systematically searched Embase, PubMed, Google Scholar, and the Cochrane Library. The analysis included prospective studies, randomized controlled trials (RCTs), and post-hoc RCT analyses reporting multivariate-adjusted associations between the NLR and survival outcomes.

Results: Elevated NLR was significantly associated with worse overall survival (HR 1.61, 95% CI 1.44-1.80) and progression-free survival (HR 1.42, 1.27-1.59). Subgroup analyses by cancer type showed consistent associations in lung (OS-HR 2.29, 1.56-3.37; PFS-HR 1.73, 1.13-2.65), colorectal (OS-HR 1.88, 1.49-2.36; PFS-HR 1.43, 1.12-1.82), gastric (OS-HR 1.65, 1.46-1.87; PFS-HR 1.88, 1.14-3.11), and breast cancers (OS-HR 1.53, 1.27-1.83; PFS-HR 1.45, 1.29-1.64). Analysis by treatment modality revealed differential prognostic effects, including for chemotherapy (OS-HR 1.48, 1.34-1.65; PFS-HR 1.34, 1.14-1.57), immunotherapy (OS-HR 3.07, 1.65-5.71; PFS-HR 1.94, 1.12-3.36), surgery (OS-HR 1.90, 1.44-2.52), and targeted therapy plus chemotherapy (OS-HR 1.56, 1.28-1.90; PFS-HR 1.46, 1.22-1.76).

Conclusion: An elevated NLR is associated with inferior clinical outcomes across multiple cancers, with the magnitude of its prognostic impact varying by treatment modality.

This study aimed to assess the diagnostic utility of routine laboratory biomarkers in adults with mTBI. We conducted a prospective study of patients who were admitted to the neurosurgical department with mTBI, had admission laboratory data available, and a brain CT scan was performed. The cohort included 101 patients (mean age: 59 ± 23.14 years). Falls were the most frequent mechanism of TBI (73.2%). Subdural hematoma (SDH) was the most frequent type of intracranial injury (31.7%), followed by contusions (28.7%), and subarachnoid hemorrhage (22.7%). Patients with intracranial trauma had higher neutrophil-to- lymphocyte (NLR) ratio (p = 0.042) and higher glucose levels (p = 0.021) than patients with concussion. Additionally, patients with SDH had significantly higher NLR and glucose levels than patients with other intracranial trauma concussion. ROC analysis showed that NLR and glucose discriminated SDH from contusion with AUCs of 0.74 (95% CI: 0.59 - 0.89) and 0.80 (95% CI: 0.7-0.9), respectively. These findings require validation in larger cohorts and suggest a meaningful role of routine biomarkers in the emergency management of mTBI. However, the single-center design and modest sample size, exclusion of patients suffering from multiple injuries, diabetes or hematologic diseases may affect measured associations.

Background: Metformin-sulfonylurea combination is a widely prescribed as second-line therapy for type 2 diabetes mellitus (T2DM), yet patient responses vary due to individual genetic variation. These variations, particularly in AMP-activated protein kinase (AMPK) and its upstream regulator liver kinase B1 (LKB1), may contribute to differences in treatment response. This study investigated the association of PRKAA2(rs2746338) and LKB1(rs741765) polymorphisms with metformin-sulfonylurea response in T2DM patients.

Methods: We enrolled 193 T2DM patients on metformin-sulfonylurea therapy after obtaining written consent. Glycemic and lipid parameters were assessed at baseline and after 3 months. Genotyping was performed by PCR-RFLP and ARMS-PCR for PRKAA2(rs2746338) and LKB1(rs741765), respectively. Statistical analysis was conducted using SPSS v27.

Results: Genotype and allele distributions were not significantly different between responders and non-responders. Carriers of PRKAA2(rs2746338) AA and AG and LKB1(rs741765) CT genotypes showed greater FBG reduction (p = 0.028, p < 0.001, and p < 0.001 respectively). Additionally, PRKAA2(rs2746338) AG and LKB1(rs741765) CT genotypes showed significant improvements in PPG, HbA1c, triglycerides, and LDL (all p < 0.05).

Conclusion: We conclude that PRKAA2(rs2746338) and LKB1(rs741765) variants were linked to favorable glycemic and lipid changes, suggesting reduced cardiovascular risk in T2DM. These variants may serve as pharmacogenetic markers for personalized therapy, warranting validation in larger studies.

Aims: This study aimed to evaluate urinary C-megalin in relation to disease staging and diagnostic accuracy in Indian patients with type 2 diabetes mellitus (T2DM).

Materials and methods: In this cross-sectional study, 325 participants were classified into No-DKD, early-DKD, and late-DKD based on kidney disease improving global outcomes (KDIGO) criteria. Urinary C-megalin was quantified by enzyme-linked immunosorbent assay (ELISA) as absolute and creatinine-normalized values. Group comparisons, correlation analyses, and multinomial logistic regression were performed to assess associations with disease stage.

Results: Creatinine-normalized C-megalin excretion was higher in early-DKD compared with No-DKD (median 125.0 vs. 92.0 ng/mg Cr; p = 0.02) and independently associated with early disease [odds ratio (OR) = 1.26, 95% confidence interval (CI): 1.03-1.55; p = 0.02). In late-DKD, absolute C-megalin levels were significantly associated with disease status (OR = 1.23, 95% CI: 1.02-1.48; p = 0.03), while normalized values lost significance. Diagnostic evaluation showed moderate accuracy for detecting early-DKD [area under curve (AUC): 0.69, 95% CI: 0.62-0.76, p = 0.001).

Conclusion: Urinary C-megalin demonstrates stage-dependent diagnostic behavior in DKD, suggesting potential as a complementary marker for early tubular injury and advanced disease in high-risk diabetic populations.

The use of biomarkers in nonclinical species has gained significant attention for improving predictive accuracy in toxicological studies and early disease detection. This article focuses on glutamate dehydrogenase (GLDH), a mitochondrial enzyme currently under regulatory review for qualification as a clinical biomarker to detect hepatocellular injury in patients with elevated serum transaminases due to muscle injury. GLDH has shown effectiveness in evaluating liver injury, particularly in rodents and non-human primates. This opinion paper outlines the potential of GLDH as a biomarker for monitoring drug-induced liver injury (DILI), drawing on the expertise of authors from the IQ DILI Initiative. It highlights industry consensus on GLDH use in nonclinical studies and its relevance in toxicology and drug development. The advantages and challenges of GLDH are discussed, including its interpretation as a mechanistic biomarker with translational relevance. Recent advancements in GLDH research in nonclinical species with different disease backgrounds and therapeutic modalities are explored. The integration of GLDH with other biomarkers to enhance the overall assessment of nonclinical species is reviewed. Our collective consensus opinion on GLDH is that it may offer an additional benefit over traditional biomarkers for hepatotoxicity, particularly when test articles cause increased serum transaminases due to concurrent muscle injury.

Aims: As primary hepatocellular carcinoma (HCC) is a prevalent digestive tract malignancy, identifying novel biomarkers for early diagnosis and prognosis is crucial. This study combined specific miRNAs with the GALAD model to create a new diagnostic model for hepatitis B virus (HBV)-related HCC.

Patients & methods: From 2020 to 2022, 884 patients from Zhongshan Hospital were enrolled, including 430 HBV-related HCC, 275 HBV-related chronic liver disease (CLD), and 179 healthy donors (HD). Stepwise regression selected features, and multivariable logistic regression built the GALADM model. A nomogram integrating age, gender, serum markers, and a score derived from seven plasma cell-free microRNAs (miRNA7) was developed.

Results: MiRNA7 value was higher in HCC patients and rose with disease progression. The GALADM model showed superior diagnostic performance, with AUCs of 0.87, 0.96, and 0.90 when distinguishing HCC from CLD, HD, and CLD+HD, outperforming the GALAD model and single markers. It also excelled in diagnosing early-stage and Alpha-fetoprotein (AFP)-negative HCC. The nomogram had an AUC of 0.977 and proved clinically useful.

Conclusion: The GALADM model, combining miRNA7 with the GALAD model, surpasses the original GALAD model, enabling early-stage and AFP-negative HCC diagnosis.